It is common knowledge that the cost of Medicare and Medicaid will grow to become an unsustainably large part of the US federal budget in coming decades. Perhaps less well known is that more than 80 percent of the projected increases derive from “excess cost growth,” unrelated to expansion in coverage or the effects of an ageing population. Excess cost growth refers to the fact that the cost of treating each beneficiary is growing faster than the growth in nominal US per capita GDP.1 In other words, the problem stems from it becoming more and more expensive to treat each person and not increases in the number of people covered. It’s the cost (not the demography) stupid!
It was therefore encouraging that the recently passed $787 billion stimulus package included $1.1 billion for funding comparative research into the relative efficiency of different drugs, medical devices, or surgical procedures for treating the same specific condition.2 The aim is to steer healthcare expenditures toward the most cost-effective treatment methods. This type of comparative analysis is often revealing.
However, given the scale of the cost challenges facing the healthcare system, the scope of the comparative cost analysis program in the stimulus package was strikingly timid. A far more informative comparative analysis would focus on contrasting the costs of different healthcare systems rather than just treatment options; in other words between the levels of total healthcare spending versus outcomes in different countries.
This is done in figures 1 and 2, which compare the total per capita healthcare spending in the United States and Europe (the x-axis) with two intuitive quality indicators of national healthcare outcomes (the y-axis). Figure 1 compares “healthy life expectancy”: the average number of years people can expect to live without serious health problems, while figure 2 compares infant mortality rates.3 The sizes of the bubbles in each figure indicate the share of total healthcare expenditures in each country that comes from the private sector.
Figures 1 and 2 illustrate several things. First of all, they show that the United States spends far more per capita, over $2,000 more based on purchasing power parity, on healthcare than any European country. Second, Americans receive relatively few benefits from this spending. At 69 years, healthy life expectancy in the United States is on par with that of Portugal, a country that spends only one third of what the United States spends on healthcare, and 3 to 4 years lower than most rich EU countries, despite the significantly lower total healthcare spending in these countries. The picture is even worse for infant mortality rates. The US infant mortality rate of 6.9 per 1000 live births is higher than any rich European country and is nearly twice the EU-15 average of 4.0 per 1000 live births, again despite the United States’ significantly higher healthcare spending.
Third, figures 1 and 2 show a clear trade-off in Europe between healthcare expenditures and outcomes, and relative efficiency levels are thus in the aggregate reasonably comparable.4 A given level of expenditure yields a given level of healthy life expectancy and infant mortality in Europe. However, the efficiency of healthcare spending in the United States is much lower. It is thus striking that the US healthcare system, which is far more reliant on private-sector spending as illustrated by the size of the bubbles in figures 1 and 2, is far less efficient than European countries’ systems.
A number of factors could contribute to the difference between the United States and Europe in the costs of their healthcare systems. But at the very least, the data suggest that “socialized medicine” in Europe fares well in containing costs.
1. Usually, the percentage by which the growth in healthcare spending (per capita) exceed the growth of nominal GDP (per capita).
2. New York Times, “US To Compare Medical Treatments,” February 16, 2009.
3. The starting point of healthy life expectancy estimates is in standard life tables providing the mortality level and life expectancy of a given population. Regular life expectancy estimates are then augmented by estimates of the number of healthy years of life lost to a comprehensive list of health conditions. In the World Health Organization data utilized here, survey data on the incidence of 135 disease and injury categories are combined with medically determined severity distributions of the 135 categories and are used to provide as comprehensive a picture as possible of the morbidity (rather than merely the mortality) statistics of the included populations.
4. Trend lines in figures 1 and 2 do not include the United States.